A ridiculous measure, because it depends upon the definition of "correct", which is an arbitrary reduction of continuous data to a single axis, and because the scoring is conducted by those who have a vested interest in the outcome, and that's just for starters.
How about applying some statistics, like the probability that a correct forecast (whatever that is) could be accounted for by chance, given the population of forecasts and conditions in which it takes place? P-values have their limitations, but that's no reason to discard them entirely.